linear_inequalities.h

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// Author(s): Jeroen Keiren and Jan Friso Groote
// Copyright: see the accompanying file COPYING or copy at
// https://github.com/mCRL2org/mCRL2/blob/master/COPYING
//
// Distributed under the Boost Software License, Version 1.0.
// (See accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt)
//
 
 
#ifndef MCRL2_DATA_LINEAR_INEQUALITY_H
#define MCRL2_DATA_LINEAR_INEQUALITY_H
 
#include "mcrl2/data/rewriter.h"
#include "mcrl2/data/substitutions/map_substitution.h"
 
namespace mcrl2
{
 
namespace data
{
 
// Functions below should be made available in the data library.
data_expression& real_zero();
data_expression& real_one();
data_expression& real_minus_one();
data_expression min(const data_expression& e1,const data_expression& e2,const rewriter&);
data_expression max(const data_expression& e1,const data_expression& e2,const rewriter&);
bool is_closed_real_number(const data_expression& e);
bool is_negative(const data_expression& e,const rewriter& r);
bool is_positive(const data_expression& e,const rewriter& r);
bool is_zero(const data_expression& e);
 
 
// Efficient construction of times on reals.
// The functions times, divide, plus, minus, negate and abs in the data library are not efficient since they determine the sort at runtime.
inline application real_times(const data_expression& arg0, const data_expression& arg1)
{
  static function_symbol times_f(sort_real::times(sort_real::real_(), sort_real::real_()));
  assert(arg0.sort()==sort_real::real_() && arg1.sort()==sort_real::real_());
  return application(times_f,arg0,arg1);
}
 
inline application real_plus(const data_expression& arg0, const data_expression& arg1)
{
  static function_symbol plus_f(sort_real::plus(sort_real::real_(), sort_real::real_()));
  assert(arg0.sort()==sort_real::real_() && arg1.sort()==sort_real::real_());
  return application(plus_f,arg0,arg1);
}
 
inline application real_divides(const data_expression& arg0, const data_expression& arg1)
{
  static function_symbol divides_f(sort_real::divides(sort_real::real_(), sort_real::real_()));
  assert(arg0.sort()==sort_real::real_() && arg1.sort()==sort_real::real_());
  return application(divides_f,arg0,arg1);
}
 
inline application real_minus(const data_expression& arg0, const data_expression& arg1)
{
  static function_symbol minus_f(sort_real::minus(sort_real::real_(), sort_real::real_()));
  assert(arg0.sort()==sort_real::real_() && arg1.sort()==sort_real::real_());
  return application(minus_f,arg0,arg1);
}
 
inline application real_negate(const data_expression& arg)
{
  static function_symbol negate_f(sort_real::negate(sort_real::real_()));
  assert(arg.sort()==sort_real::real_());
  return application(negate_f,arg);
}
 
inline application real_abs(const data_expression& arg)
{
  static function_symbol abs_f(sort_real::abs(sort_real::real_()));
  assert(arg.sort()==sort_real::real_());
  return application(abs_f,arg);
}
 
// End of functions that ought to be defined elsewhere.
 
 
inline data_expression rewrite_with_memory(const data_expression& t,const rewriter& r);
 
// prototype
class linear_inequality;
namespace detail
{
  class lhs_t;
}
 
inline std::string pp(const linear_inequality& l);
template <class TYPE>
inline std::string pp_vector(const TYPE& inequalities);
 
namespace detail
{
  enum comparison_t { less, less_eq, equal };
 
  inline std::string pp(const detail::lhs_t& lhs);
 
  inline detail::comparison_t negate(const detail::comparison_t t)
  {
    switch (t)
    {
      case detail::less:  return detail::less_eq;
      case detail::less_eq: return detail::less;
      case detail::equal: return detail::equal;
    };
    return detail::equal;  // This return statement should be unreachable. It is added to suppress a compiler warning.
  }
 
  inline std::string pp(const detail::comparison_t t)
  {
    switch (t)
    {
      case detail::less:  return "<";
      case detail::less_eq: return "<=";
      case detail::equal: return "==";
    };
    return "##";  // This return statement should be unreachable. It is added to suppress a compiler warning.
  }
 
  inline atermpp::function_symbol f_variable_with_a_rational_factor()
  {
    static atermpp::function_symbol f("variable_with_a_rational_factor",2);
    return f;
  }
 
  class variable_with_a_rational_factor: public atermpp::aterm
  {
    public:
      // \brief default constructor
      variable_with_a_rational_factor(const variable& v, const data_expression& f)
       : atermpp::aterm(f_variable_with_a_rational_factor(),v,f)
      {
        assert(f!=real_zero());
      }
 
     // \brief Get the variable in a variable/rational factor pair.
     const variable& variable_name() const
     {
       assert(is_variable_with_a_rational_factor());
       return atermpp::down_cast<variable>((*this)[0]);
     }
 
     // \brief Get the rational factor in a variable/rational factor pair.
     const data_expression& factor() const
     {
       assert(is_variable_with_a_rational_factor());
       return atermpp::down_cast<data_expression>((*this)[1]);
     }
 
     // \brief Check that a term is indeed a variable with a rational factor pair.
     bool is_variable_with_a_rational_factor() const
     {
       return function()==f_variable_with_a_rational_factor();
     }
 
     // \brief Transform the variable with factor to a data_expression.
     data_expression transform_to_data_expression() const
     {
       return real_times(factor(),variable_name());
     }
  };
 
  // typedef atermpp::term_list<variable_with_a_rational_factor> lhs_t;
  typedef std::map < variable, data_expression > map_based_lhs_t;
 
  class lhs_t: public atermpp::term_list<variable_with_a_rational_factor>
  {
    public:
      lhs_t()
       : atermpp::term_list<variable_with_a_rational_factor>()
      {}
 
      explicit lhs_t(const aterm& t)
       : atermpp::term_list<variable_with_a_rational_factor>(t)
      {}
 
      template <class ITERATOR>
      lhs_t(const ITERATOR begin, const ITERATOR end)
       : atermpp::term_list<variable_with_a_rational_factor>(begin, end)
      {}
 
      template <class ITERATOR, class TRANSFORMER>
      lhs_t(const ITERATOR begin, const ITERATOR end, TRANSFORMER f)
       : atermpp::term_list<variable_with_a_rational_factor>(begin, end, f)
      {}
 
      lhs_t::const_iterator find(const variable& v) const
      {
        return std::find_if(begin(),
                            end(),
                            [&](const detail::variable_with_a_rational_factor& p)
                                                    {return p.variable_name()==v;});
      }
 
      lhs_t erase(const variable& v) const
      {
        std::vector <variable_with_a_rational_factor> result;
        for(const variable_with_a_rational_factor& p: *this)
        {
          if (p.variable_name()!=v)
          {
            result.push_back(p);
          }
        }
        return lhs_t(result.begin(),result.end());
      }
 
      const data_expression& operator[](const variable& v) const
      {
        lhs_t::const_iterator i=find(v);
        if (i==end())  // Not found.
        {
          return real_zero();
        }
        return i->factor();
      }
 
      std::size_t count(const variable& v) const
      {
        lhs_t::const_iterator i=find(v);
        if (i==end())  // Not found.
        {
          return 0;
        }
        return 1;
      }
 
      template <typename SubstitutionFunction>
      data_expression evaluate(const SubstitutionFunction& beta, const rewriter& r) const
      {
        data_expression result=real_zero();
        bool result_defined=false; // save adding the initial zero.
        for (const variable_with_a_rational_factor& p: *this)
        {
          if (result_defined)
          {
            result=rewrite_with_memory(real_plus(result,real_times(beta(p.variable_name()),p.factor())), r);
          }
          else
          {
            result=rewrite_with_memory(real_times(beta(p.variable_name()),p.factor()), r);
            result_defined=true;
          }
 
        }
        return result;
      }
 
     // \brief Transform this lhs to a data_expression.
     data_expression transform_to_data_expression() const
     {
       if (size()==0)
       {
         return real_zero();
       }
       data_expression result=real_zero();
 
       for(const variable_with_a_rational_factor& p: *this)
       {
         if (result==real_zero())
         {
           result=p.transform_to_data_expression();
         }
         else
         {
           result=real_plus(result,p.transform_to_data_expression());
         }
       }
       return result;
     }
  };
 
  inline void set_factor_for_a_variable(detail::map_based_lhs_t& new_lhs, const variable& x, const data_expression& e)
  {
    assert(is_closed_real_number(e));
    if (e==real_zero())
    {
      detail::map_based_lhs_t::iterator i=new_lhs.find(x);
      if (i!=new_lhs.end())
      {
        new_lhs.erase(i);
      }
    }
    else
    {
      new_lhs[x]=e;
    }
  }
 
  inline lhs_t set_factor_for_a_variable(const lhs_t& lhs, const variable& x, const data_expression& e)
  {
    assert(is_closed_real_number(e));
    bool inserted=false;
    std::vector<variable_with_a_rational_factor> result;
    for(const variable_with_a_rational_factor& p: lhs)
    {
      if (!inserted && x<=p.variable_name())
      {
        result.emplace_back(x,e);
        inserted=true;
        if (x!=p.variable_name())
        {
          result.emplace_back(p.variable_name(),p.factor());
        }
      }
      else result.emplace_back(p.variable_name(),p.factor());
    }
    if (!inserted)
    {
        result.emplace_back(x,e);
    }
    assert(std::find(result.begin(),result.end(),variable_with_a_rational_factor(x,e))!=result.end());
    return lhs_t(result.begin(),result.end());
  }
 
  inline const lhs_t map_to_lhs_type(const map_based_lhs_t& lhs)
  {
    lhs_t result;
    for(map_based_lhs_t::const_reverse_iterator i=lhs.rbegin(); i!=lhs.rend(); ++i)
    {
        result.push_front(variable_with_a_rational_factor(i->first,i->second));
    }
    return result;
  }
 
  inline const lhs_t map_to_lhs_type(const map_based_lhs_t& lhs, const data_expression& factor, const rewriter& r)
  {
    assert(factor!=real_one() && factor!=real_minus_one());
    lhs_t result;
    for(map_based_lhs_t::const_reverse_iterator i=lhs.rbegin(); i!=lhs.rend(); ++i)
    {
      result.push_front(variable_with_a_rational_factor(i->first, rewrite_with_memory(real_divides(i->second,factor), r)));
    }
    return result;
  }
 
  inline bool is_well_formed(const lhs_t& lhs)
  {
    if (lhs.empty())
    {
      return true;
    }
    if (lhs.front().factor()!=real_one() && lhs.front().factor()!=real_minus_one())
    {
      return false;
    }
    variable last_variable_seen=lhs.front().variable_name();
    bool first=true;
    for(const variable_with_a_rational_factor& p: lhs)
    {
      if (!first)
      {
        first=false;
        if (p.variable_name()<=last_variable_seen)
        {
          return false;
        }
        last_variable_seen=p.variable_name();
      }
    }
    return true;
  }
 
  inline const lhs_t remove_variable_and_divide(const lhs_t& lhs, const variable& v, const data_expression& f, const rewriter& r)
  {
    std::vector <variable_with_a_rational_factor> result;
    for(const variable_with_a_rational_factor& p: lhs)
    {
      if (p.variable_name()!=v)
      {
        result.emplace_back(p.variable_name(),rewrite_with_memory(real_divides(p.factor(),f), r));
      }
    }
    return lhs_t(result.begin(),result.end());
  }
 
  inline void emplace_back_if_not_zero(std::vector<detail::variable_with_a_rational_factor>& r, const variable& v, const data_expression& f)
  {
    if (f!=real_zero())
    {
      r.emplace_back(v,f);
    }
  }
 
 
  template < application Operation(const data_expression&, const data_expression&) >
  inline const lhs_t meta_operation_constant(const lhs_t& argument, const data_expression& v, const rewriter& r)
  {
    std::vector<detail::variable_with_a_rational_factor> result;
    result.reserve(argument.size());
    for (const detail::variable_with_a_rational_factor& p: argument)
    {
      emplace_back_if_not_zero(result,p.variable_name(), rewrite_with_memory(Operation(v,p.factor()),r));
    }
    return lhs_t(result.begin(),result.end());
  }
 
  // Template method to add or subtract lhs_t's
  // template < application Operation(const data_expression&, const data_expression&) >
  template <class OPERATION>
  inline lhs_t meta_operation_lhs(const lhs_t& argument1,
                                  const lhs_t& argument2,
                                  OPERATION operation,
                                  const rewriter& r)
  {
    std::vector<detail::variable_with_a_rational_factor> result;
    result.reserve(argument1.size()+argument2.size());
 
    lhs_t::const_iterator i1=argument1.begin();
    lhs_t::const_iterator i2=argument2.begin();
 
    while (i1!=argument1.end() && i2!=argument2.end())
    {
      if (i1->variable_name()<i2->variable_name())
      {
        emplace_back_if_not_zero(result,i1->variable_name(), rewrite_with_memory(operation(i1->factor(),real_zero()),r));
        ++i1;
      }
      else if (i1->variable_name()>i2->variable_name())
      {
        emplace_back_if_not_zero(result,i2->variable_name(), rewrite_with_memory(operation(real_zero(),i2->factor()),r));
        ++i2;
      }
      else
      {
        assert(i1->variable_name()==i2->variable_name());
        emplace_back_if_not_zero(result,i1->variable_name(), rewrite_with_memory(operation(i1->factor(),i2->factor()),r));
        ++i1;
        ++i2;
      }
    }
 
    if (i1==argument1.end())
    {
      while (i2!=argument2.end())
      {
        emplace_back_if_not_zero(result,i2->variable_name(), rewrite_with_memory(operation(real_zero(),i2->factor()),r));
        ++i2;
      }
    }
    else
    {
      while (i1!=argument1.end())
      {
        emplace_back_if_not_zero(result,i1->variable_name(), rewrite_with_memory(operation(i1->factor(),real_zero()),r));
        ++i1;
      }
    }
    return lhs_t(result.begin(),result.end());
  }
 
  inline const lhs_t add(const data_expression& v, const lhs_t& argument, const rewriter& r)
  {
    return meta_operation_constant<real_plus>(argument,v,r);
  }
 
  inline const lhs_t subtract(const lhs_t& argument, const data_expression& v, const rewriter& r)
  {
    return meta_operation_constant<real_minus>(argument, v, r);
  }
 
  inline const lhs_t multiply(const lhs_t& argument, const data_expression& v, const rewriter& r)
  {
    return meta_operation_constant<real_times>(argument, v, r);
  }
 
  inline const lhs_t divide(const lhs_t& argument, const data_expression& v, const rewriter& r)
  {
    return meta_operation_constant<real_divides>(argument, v, r);
  }
 
  inline const lhs_t add(const lhs_t& argument, const lhs_t& e, const rewriter& r)
  {
    return meta_operation_lhs(argument,
                              e,
                              [](const data_expression& d1, const data_expression& d2)->data_expression
                                              { return real_plus(d1,d2); },
                              r);
  }
 
  inline const lhs_t subtract(const lhs_t& argument, const lhs_t& e, const rewriter& r)
  {
    return meta_operation_lhs(argument,
                              e,
                              [](const data_expression& d1, const data_expression& d2)->data_expression
                                              { return real_minus(d1,d2); },
                              r);
  }
 
  inline std::string pp(const lhs_t& lhs)
  {
    std::string s;
    if (lhs.begin()==lhs.end())
    {
      s="0";
    }
    for (lhs_t::const_iterator i=lhs.begin(); i!=lhs.end(); ++i)
    {
      s=s + (i==lhs.begin()?"":" + ") ;
 
      if (i->factor()==real_one())
      {
        s=s + pp(i->variable_name());
      }
      else if (i->factor()==real_minus_one())
      {
        s=s + "-" + pp(i->variable_name());
      }
      else
      {
        s=s + data::pp(i->factor()) + "*" + data::pp(i->variable_name());
      }
    }
    return s;
  }
 
  inline atermpp::function_symbol linear_inequality_less()
  {
    static atermpp::function_symbol f("linear_inequality_less",2);
    return f;
  }
 
 
  inline atermpp::function_symbol linear_inequality_less_equal()
  {
    static atermpp::function_symbol f("linear_inequality_less_equal",2);
    return f;
  }
 
 
  inline atermpp::function_symbol linear_inequality_equal()
  {
    static atermpp::function_symbol f("linear_inequality_equal",2);
    return f;
  }
 
} // end namespace detail
 
class linear_inequality: public atermpp::aterm
{
  // The structure of a linear equality is a function application
  // to two arguments. The function application is either linear_inequality_less,
  // linear_inequality_less_equal, or linear_inequality_equal. There are two arguments,
  // namely an ordered list of pairs of a variable and a factor. This list is ordered
  // on the variables, and a closed expression which forms the right hand side.
  // The first variable in the list has a factor one or minus one.
 
  protected:
 
    static void parse_and_store_expression(
      const data_expression& e,
      detail::map_based_lhs_t& new_lhs,
      data_expression& new_rhs,
      const rewriter& r,
      const bool negate = false,
      const data_expression& factor = real_one())
    {
      if (sort_real::is_minus_application(e))
      {
        parse_and_store_expression(binary_left1(e),new_lhs,new_rhs,r,negate,factor);
        parse_and_store_expression(binary_right1(e),new_lhs,new_rhs,r,!negate,factor);
      }
      else if (sort_real::is_negate_application(e))
      {
        parse_and_store_expression(unary_operand1(e),new_lhs,new_rhs,r,!negate,factor);
      }
      else if (sort_real::is_plus_application(e))
      {
        parse_and_store_expression(binary_left1(e),new_lhs,new_rhs,r,negate,factor);
        parse_and_store_expression(binary_right1(e),new_lhs,new_rhs,r,negate,factor);
      }
      else if (sort_real::is_times_application(e))
      {
        data_expression lhs = rewrite_with_memory(binary_left1(e),r);
        data_expression rhs = rewrite_with_memory(binary_right1(e),r);
        if (is_closed_real_number(lhs))
        {
          parse_and_store_expression(rhs,new_lhs,new_rhs,r,negate,real_times(lhs,factor));
        }
        else if (is_closed_real_number(rhs))
        {
          parse_and_store_expression(lhs,new_lhs,new_rhs,r,negate,real_times(rhs,factor));
        }
        else
        {
          throw mcrl2::runtime_error("Expect constant multiplies expression: " + pp(e) + "\n");
        }
      }
      else if (is_variable(e))
      {
        const variable& v = atermpp::down_cast<variable>(e);
        if(v.sort() != sort_real::real_())
        {
          throw mcrl2::runtime_error("Encountered a variable in a real expression which is not of sort real: " + pp(e) + "\n");
        }
        const detail::map_based_lhs_t::const_iterator var_factor = new_lhs.find(v);
 
        const data_expression neg_factor(negate ? real_negate(factor) : factor);
        const data_expression new_factor(var_factor == new_lhs.end() ? neg_factor : real_plus(var_factor->second, neg_factor));
        detail::set_factor_for_a_variable(new_lhs, v, rewrite_with_memory(new_factor, r));
      }
      else if (is_closed_real_number(rewrite_with_memory(e,r)))
      {
        // We are reasoning about the rhs, so apply double negation in case 'negate' is true
        data_expression add_to_rhs(negate ? e : real_negate(e));
        if(factor != real_one())
        {
          add_to_rhs = real_times(factor, add_to_rhs);
        }
        new_rhs = rewrite_with_memory(real_plus(new_rhs, add_to_rhs), r);
      }
      else
      {
        throw mcrl2::runtime_error("Expect linear expression over reals: " + pp(e) + "\n");
      }
    }
 
 
  public:
 
    linear_inequality()
      : linear_inequality(detail::lhs_t(),real_zero(),detail::less)
    {}
 
    linear_inequality(const detail::lhs_t& lhs, const data_expression& r, detail::comparison_t t)
     : atermpp::aterm((t==detail::less?
                      detail::linear_inequality_less():
                      (t==detail::less_eq?detail::linear_inequality_less_equal():detail::linear_inequality_equal())),
                  lhs,r)
    {
      assert(detail::is_well_formed(lhs));
      assert(t==detail::less || t==detail::less_eq || t==detail::equal);
    }
 
    linear_inequality(const detail::lhs_t& lhs, const data_expression& rhs, detail::comparison_t comparison, const rewriter& r)
    {
      if (lhs.empty())
      {
        *this=linear_inequality(detail::lhs_t(),rhs,comparison);
        return;
      }
      // Normalize the linear_inequality such that the first term has factor 1 or -1.
      data_expression factor=lhs.begin()->factor();
      if (factor==real_one() || factor==real_minus_one())
      {
        *this=linear_inequality(lhs,rhs,comparison);
        return;
      }
      factor=rewrite_with_memory(real_abs(factor), r);
 
      *this=linear_inequality(divide(lhs,factor,r),rewrite_with_memory(real_divides(rhs,factor), r),comparison);
    }
 
    linear_inequality(const data_expression& lhs,
                      const data_expression& rhs,
                      const detail::comparison_t comparison,
                      const rewriter& r,
                      const bool negate=false)
    {
      detail::map_based_lhs_t new_lhs;
      data_expression new_rhs(real_zero());
      parse_and_store_expression(lhs,new_lhs,new_rhs,r,negate);
      parse_and_store_expression(rhs,new_lhs,new_rhs,r,!negate);
 
      if (new_lhs.empty())
      {
        if ((comparison==detail::equal && new_rhs==real_zero()) ||
            (comparison==detail::less_eq && (new_rhs == real_zero() || is_positive(new_rhs,r))) ||
            (comparison==detail::less && is_positive(new_rhs,r)))
        {
          // The linear inequality represents true.
          *this=linear_inequality(detail::lhs_t(),real_one(),detail::less);
          return;
        }
        // The linear inequality represents false.
        *this=linear_inequality(detail::lhs_t(),real_minus_one(),detail::less);
        return;
      }
 
      // Normalize the linear_inequality such that the first term has factor 1 or -1.
      data_expression factor=new_lhs.begin()->second;
      if (factor==real_one() || factor==real_minus_one())
      {
        *this=linear_inequality(detail::map_to_lhs_type(new_lhs),new_rhs,comparison);
        return;
      }
      factor=rewrite_with_memory(real_abs(factor), r);
 
      *this=linear_inequality(detail::map_to_lhs_type(new_lhs,factor,r),rewrite_with_memory(real_divides(new_rhs,factor), r),comparison);
    }
 
 
 
 
    linear_inequality(const data_expression& e,
                      const rewriter& r)
    {
      detail::comparison_t comparison;
      bool negate(false);
      if (is_equal_to_application(e))
      {
        comparison=detail::equal;
      }
      else if (is_less_application(e))
      {
        comparison=detail::less;
      }
      else if (is_less_equal_application(e))
      {
        comparison=detail::less_eq;
      }
      else if (is_greater_application(e))
      {
        comparison=detail::less;
        negate=true;
      }
      else if (is_greater_equal_application(e))
      {
        comparison=detail::less_eq;
        negate=true;
      }
      else
      {
        throw mcrl2::runtime_error("Unexpected equality or inequality: " + pp(e) + "\n") ;
      }
 
      data_expression lhs=data::binary_left(atermpp::down_cast<application>(e));
      data_expression rhs=data::binary_right(atermpp::down_cast<application>(e));
      *this=linear_inequality(lhs,rhs,comparison,r,negate);
 
    }
 
 
    detail::lhs_t::const_iterator lhs_begin() const
    {
      return lhs().begin();
    }
 
    detail::lhs_t::const_iterator lhs_end() const
    {
      return lhs().end();
    }
 
    const detail::lhs_t& lhs() const
    {
      return atermpp::down_cast<detail::lhs_t>((*this)[0]);
    }
 
    const data_expression& rhs() const
    {
      return atermpp::down_cast<data_expression>((*this)[1]);
    }
 
    data_expression get_factor_for_a_variable(const variable& x)
    {
      return lhs()[x];
    }
 
    detail::comparison_t comparison() const
    {
      if (this->function()==detail::linear_inequality_less())
      {
        return detail::less;
      }
      else if (this->function()==detail::linear_inequality_less_equal())
      {
        return detail::less_eq;
      }
      assert(this->function()==detail::linear_inequality_equal());
      return detail::equal;
    }
 
    data_expression transform_to_data_expression() const
    {
      const detail::comparison_t c=comparison();
      if (c==detail::less_eq)
      {
        return data::less_equal(lhs().transform_to_data_expression(),rhs());
      }
      if (c==detail::less)
      {
        return data::less(lhs().transform_to_data_expression(),rhs());
      }
      assert(c==detail::equal);
      return data::equal_to(lhs().transform_to_data_expression(),rhs());
    }
 
    bool is_false(const rewriter& r) const
    {
      return lhs().empty() &&
             ((comparison()==detail::less_eq)?is_negative(rhs(),r):
              ((comparison()==detail::equal)?!is_zero(rhs()):!is_positive(rhs(),r)));
    }
 
    bool is_true(const rewriter& r) const
    {
      return lhs().empty() &&
             ((comparison()==detail::less_eq)?!is_negative(rhs(),r):
              ((comparison()==detail::equal)?is_zero(rhs()):is_positive(rhs(),r)));
    }
 
    bool typical_pair(
      data_expression& lhs_expression,
      data_expression& rhs_expression,
      detail::comparison_t& comparison_operator,
      const rewriter& r) const
    {
      if (lhs_begin()==lhs_end())
      {
        lhs_expression=real_zero();
        rhs_expression=rhs();
        comparison_operator=comparison();
        return false;
      }
 
      data_expression factor=lhs_begin()->factor();
 
      for (detail::lhs_t::const_iterator i=lhs_begin(); i!=lhs_end(); ++i)
      {
        variable v=i->variable_name();
        data_expression e=real_times(rewrite_with_memory(real_divides(i->factor(),factor),r),
                                           data_expression(v));
        if (i==lhs_begin())
        {
          lhs_expression=e;
        }
        else
        {
          lhs_expression=real_plus(lhs_expression,e);
        }
      }
 
      rhs_expression=rewrite_with_memory(real_divides(rhs(),factor),r);
      if (is_negative(factor,r))
      {
        comparison_operator=negate(comparison());
        return true;
      }
      else
      {
        comparison_operator=comparison();
        return false;
      }
    }
 
    linear_inequality invert(const rewriter& r)
    {
      const detail::lhs_t new_lhs(lhs().begin(),
                              lhs().end(),
                              [&](const detail::variable_with_a_rational_factor& p)
                                      { return detail::variable_with_a_rational_factor(
                                                    p.variable_name(),
                                                    rewrite_with_memory(real_negate(p.factor()),r));});
 
      const data_expression new_rhs=rewrite_with_memory(real_negate(rhs()),r);
      if (comparison()==detail::less)
      {
        // set_comparison(detail::less_eq);
        return linear_inequality(new_lhs,new_rhs,detail::less_eq);
      }
      else if (comparison()==detail::less_eq)
      {
        // set_comparison(detail::less);
        return linear_inequality(new_lhs,new_rhs,detail::less);
      }
      return linear_inequality(new_lhs,new_rhs,detail::equal);
    }
 
    void add_variables(std::set < variable >&  variable_set) const
    {
      for (detail::lhs_t::const_iterator i=lhs().begin(); i!=lhs().end(); ++i)
      {
        variable_set.insert(i->variable_name());
      }
    }
};
 
inline std::string pp(const linear_inequality& l)
{
  return pp(l.lhs()) + " " + detail::pp(l.comparison()) + " " + pp(l.rhs());
}
 
//         where the comparison operator of e1 is kept.
inline linear_inequality subtract(const linear_inequality& e1,
                                  const linear_inequality& e2,
                                  const data_expression& f1,
                                  const data_expression& f2,
                                  const rewriter& r)
{
  const data_expression f=rewrite_with_memory(real_divides(f1,f2),r);
  return linear_inequality(
                detail::meta_operation_lhs(e1.lhs(),e2.lhs(),
                              [&](const data_expression& d1, const data_expression& d2)->data_expression
                                         { return real_minus(d1,real_times(f,d2)); },r),
                rewrite_with_memory(real_minus(e1.rhs(),real_times(f,e2.rhs())),r),
                e1.comparison(),
                r);
}
 
// Real zero and real one are an ad hoc solution. They should be provided by
// the data type library.
 
inline data_expression& real_zero()
{
  static data_expression real_zero=sort_real::real_("0");
  return real_zero;
}
 
inline data_expression& real_one()
{
  static data_expression real_one=sort_real::real_("1");
  return real_one;
}
 
inline data_expression& real_minus_one()
{
  static data_expression real_minus_one=sort_real::real_("-1");
  return real_minus_one;
}
 
inline data_expression min(const data_expression& e1,const data_expression& e2,const rewriter& r)
{
  if (rewrite_with_memory(less_equal(e1,e2),r)==sort_bool::true_())
  {
    return e1;
  }
  if (rewrite_with_memory(less_equal(e2,e1),r)==sort_bool::true_())
  {
    return e2;
  }
  throw mcrl2::runtime_error("Fail to determine the minimum of: " + pp(e1) + " and " + pp(e2) + "\n");
}
 
inline data_expression max(const data_expression& e1,const data_expression& e2,const rewriter& r)
{
  if (rewrite_with_memory(less_equal(e2,e1),r)==sort_bool::true_())
  {
    return e1;
  }
  if (rewrite_with_memory(less_equal(e1,e2),r)==sort_bool::true_())
  {
    return e2;
  }
  throw mcrl2::runtime_error("Fail to determine the maximum of: " + pp(e1) + " and " + pp(e2) + "\n");
}
 
inline bool is_closed_real_number(const data_expression& e)
{
  if (e.sort()!=sort_real::real_())
  {
    return false;
  }
 
  std::set < variable > s=find_all_variables(e);
  return s.empty();
}
 
inline bool is_negative(const data_expression& e,const rewriter& r)
{
  data_expression result=rewrite_with_memory(less(e,real_zero()),r);
  if (result==sort_bool::true_())
  {
    return true;
  }
  if (result==sort_bool::false_())
  {
    return false;
  }
  throw mcrl2::runtime_error("Cannot determine that " + pp(e) + " is smaller than 0");
}
 
inline bool is_positive(const data_expression& e,const rewriter& r)
{
  data_expression result=rewrite_with_memory(greater(e,real_zero()),r);
  if (result==sort_bool::true_())
  {
    return true;
  }
  if (result==sort_bool::false_())
  {
    return false;
  }
  throw mcrl2::runtime_error("Cannot determine that " + pp(e) + " is larger than or equal to 0");
}
 
inline bool is_zero(const data_expression& e)
{
  // Assume data_expression is in normal form.
  assert(is_closed_real_number(e));
  return (e==real_zero());
}
 
template <class TYPE>
inline std::string pp_vector(const TYPE& inequalities)
{
  std::string s="[";
  bool first=true;
  for (const linear_inequality& l: inequalities)
  {
    s=s+ (first?"":", ") + pp(l);
    first=false;
  }
  s=s+ "]";
  return s;
}
 
bool is_inconsistent(
  const std::vector < linear_inequality >& inequalities_in,
  const rewriter& r,
  const bool use_cache=true);
 
 
// Count the occurrences of variables that occur in inequalities.
inline
void count_occurrences(
  const std::vector < linear_inequality >& inequalities,
  std::map < variable, std::size_t>& nr_positive_occurrences,
  std::map < variable, std::size_t>& nr_negative_occurrences,
  const rewriter& r)
{
  for (std::vector < linear_inequality >::const_iterator i=inequalities.begin();
       i!=inequalities.end(); ++i)
  {
    for (detail::lhs_t::const_iterator j=i->lhs_begin(); j!=i->lhs_end(); ++j)
    {
      if (is_positive(j->factor(),r))
      {
        nr_positive_occurrences[j->variable_name()]=nr_positive_occurrences[j->variable_name()]+1;
      }
      else
      {
        nr_negative_occurrences[j->variable_name()]=nr_negative_occurrences[j->variable_name()]+1;
      }
    }
  }
}
 
template < class Variable_iterator >
std::set < variable >  gauss_elimination(
  const std::vector < linear_inequality >& inequalities,
  std::vector < linear_inequality >& resulting_equalities,
  std::vector < linear_inequality >& resulting_inequalities,
  Variable_iterator variables_begin,
  Variable_iterator variables_end,
  const rewriter& r);
 
 
 
inline bool is_a_redundant_inequality(
  const std::vector < linear_inequality >& inequalities,
  const std::vector < linear_inequality > :: iterator i,
  const rewriter& r)
{
#ifndef NDEBUG
  // Check that i points to some position in inequalities.
  bool found=false;
  for (std::vector < linear_inequality >:: const_iterator j=inequalities.begin() ;
       j!=inequalities.end() ; ++j)
  {
    if (j==i)
    {
      found=true;
      break;
    }
  }
  assert(found);
#endif
  // Check whether the inequalities, with the i-th equality with a reversed comparison operator is inconsistent.
  // If yes, the i-th inequality is redundant.
  if (i->comparison()==detail::equal)
  {
    // An inequality t==u is only redundant for equalities if
    // t<u and t>u are both inconsistent
    const linear_inequality old_inequality=*i;
    *i=linear_inequality(i->lhs(),i->rhs(),detail::less);
    if (is_inconsistent(inequalities,r))
    {
      *i=i->invert(r);
      if (is_inconsistent(inequalities,r))
      {
        *i=old_inequality;
        return true;
      }
    }
    *i=old_inequality;
    return false;
  }
  else
  {
    // an inequality t<u, t<=u, t>u and t>=u is redundant in equalities
    // if its inversion is inconsistent.
    const linear_inequality old_inequality=*i;
    *i=i->invert(r);
    if (is_inconsistent(inequalities,r))
    {
      *i=old_inequality;
      return true;
    }
    else
    {
      *i=old_inequality;
      return false;
    }
  }
}
 
//                                Initially this list must be empty.
 
inline void remove_redundant_inequalities(
  const std::vector < linear_inequality >& inequalities,
  std::vector < linear_inequality >& resulting_inequalities,
  const rewriter& r)
{
  assert(resulting_inequalities.empty());
  if (inequalities.empty())
  {
    return;
  }
 
  // If false is among the inequalities, [false] is the minimal result.
  if (is_inconsistent(inequalities,r))
  {
    resulting_inequalities.push_back(linear_inequality());
    return;
  }
 
  resulting_inequalities=inequalities;
  for (std::size_t i=0; i<resulting_inequalities.size();)
  {
    // Check whether the inequalities, with the i-th equality with a reversed comparison operator is inconsistent.
    // If yes, the i-th inequality is redundant.
    if (resulting_inequalities[i].comparison()==detail::equal)
    {
      // Do nothing, as removing redundant inequalities is expensive.
      ++i;
    }
    else
    {
      if (is_a_redundant_inequality(resulting_inequalities,
                                    resulting_inequalities.begin()+i,
                                    r))
      {
        /* The code below does not preserve the ordering in inequalities.
        if (i+1<resulting_inequalities.size())
        {
          // Copy the last element to the current position.
          resulting_inequalities[i].swap(resulting_inequalities.back());
        }
        resulting_inequalities.pop_back(); */
        resulting_inequalities.erase(resulting_inequalities.begin()+i);
      }
      else
      {
        ++i;
      }
    }
  }
}
 
//---------------------------------------------------------------------------------------------------
 
static void pivot_and_update(
  const variable& xi,  // a basic variable
  const variable& xj,  // a non basic variable
  const data_expression& v,
  const data_expression& v_delta_correction,
  std::map < variable,data_expression >& beta,
  std::map < variable,data_expression >& beta_delta_correction,
  std::set < variable >& basic_variables,
  std::map < variable, detail::lhs_t >& working_equalities,
  const rewriter& r)
{
  mCRL2log(log::trace) << "Pivoting " << pp(xi) << "   " << pp(xj) << "\n";
  const data_expression aij=working_equalities[xi][xj];
  const data_expression theta=rewrite_with_memory(real_divides(real_minus(v,beta[xi]),aij),r);
  const data_expression theta_delta_correction=rewrite_with_memory(real_divides(real_minus(v,beta_delta_correction[xi]),aij),r);
  beta[xi]=v;
  beta_delta_correction[xi]=v_delta_correction;
  beta[xj]=rewrite_with_memory(real_plus(beta[xj],theta),r);
  beta_delta_correction[xj]=rewrite_with_memory(real_plus(beta_delta_correction[xj],theta_delta_correction),r);
 
  mCRL2log(log::trace) << "Pivoting phase 0\n";
  for (std::set < variable >::const_iterator k=basic_variables.begin();
       k!=basic_variables.end(); ++k)
  {
    mCRL2log(log::trace) << "Working equalities " << *k << ":  " << pp(working_equalities[*k]) << "\n";
    if ((*k!=xi) && (working_equalities[*k].count(xj)>0))
    {
      const data_expression akj=working_equalities[*k][xj];
      beta[*k]=rewrite_with_memory(real_plus(beta[*k],real_times(akj ,theta)),r);
      beta_delta_correction[*k]=rewrite_with_memory(real_plus(beta_delta_correction[*k],real_times(akj ,theta_delta_correction)),r);
    }
  }
  // Apply pivoting on variables xi and xj;
  mCRL2log(log::trace) << "Pivoting phase 1\n";
  basic_variables.erase(xi);
  basic_variables.insert(xj);
 
  detail::lhs_t expression_for_xj=working_equalities[xi];
  expression_for_xj=expression_for_xj.erase(xj);
  expression_for_xj=set_factor_for_a_variable(expression_for_xj,xi,real_minus_one());
  expression_for_xj=multiply(expression_for_xj,real_divides(real_minus_one(),aij),r);
  mCRL2log(log::trace) << "Expression for xj:" << pp(expression_for_xj) << "\n";
  mCRL2log(log::trace) << "Pivoting phase 2\n";
  working_equalities.erase(xi);
 
  for (std::map < variable, detail::lhs_t >::iterator j=working_equalities.begin();
       j!=working_equalities.end(); ++j)
  {
    if (j->second.count(xj)>0)
    {
      const data_expression factor=j->second[xj];
      mCRL2log(log::trace) << "VAR: " << pp(j->first) << " Factor " << pp(factor) << "\n";
      j->second=j->second.erase(xj);
      // We need a temporary copy of expression_for_xj as otherwise the multiply
      // below will change this expression.
      //detail::lhs_t temporary_expression_for_xj(expression_for_xj);
      j->second=add(j->second,multiply(expression_for_xj,factor,r),r);
    }
  }
 
  working_equalities[xj]=expression_for_xj;
 
  mCRL2log(log::trace) << "Pivoting phase 3\n";
  // Calculate the values for beta and beta_delta_correction for the basic variables
  for (std::map < variable, detail::lhs_t >::const_iterator i=working_equalities.begin();
       i!=working_equalities.end() ; ++i)
  {
    beta[i->first]=i->second.evaluate(make_map_substitution(beta),r);
    beta_delta_correction[i->first]=i->second.evaluate(make_map_substitution(beta_delta_correction),r);
  }
 
  mCRL2log(log::trace) << "End pivoting " << pp(xj) << "\n";
  if (mCRL2logEnabled(log::trace))
  {
    for (std::map < variable,data_expression >::const_iterator i=beta.begin();
         i!=beta.end(); ++i)
    {
      mCRL2log(log::trace) << "(1) beta[" << pp(i->first) << "]= " << pp(beta[i->first]) << "+ delta* " << pp(beta_delta_correction[i->first]) << "\n";
    }
    for (std::map < variable, detail::lhs_t >::const_iterator i=working_equalities.begin();
         i!=working_equalities.end() ; ++i)
    {
      mCRL2log(log::trace) << "EQ: " << pp(i->first) << " := " << pp(i->second) << "\n";
    }
  }
}
 
namespace detail
{
  /* False end nodes could be associated with NULL */
  typedef enum { true_end_node, false_end_node, intermediate_node } node_type;
  class inequality_inconsistency_cache;
  class inequality_consistency_cache;
 
  class inequality_inconsistency_cache_base
  {
    friend inequality_inconsistency_cache;
    friend inequality_consistency_cache;
 
    protected:
      node_type m_node;
      linear_inequality m_inequality;
      inequality_inconsistency_cache_base* m_present_branch;
      inequality_inconsistency_cache_base* m_non_present_branch;
 
    public:
 
      inequality_inconsistency_cache_base(const inequality_inconsistency_cache_base& )=delete;
      inequality_inconsistency_cache_base& operator=(const inequality_inconsistency_cache_base& )=delete;
 
      inequality_inconsistency_cache_base(const node_type node)
        : m_node(node), m_present_branch(), m_non_present_branch()
      {}
 
      inequality_inconsistency_cache_base(
                  const node_type node,
                  const linear_inequality& inequality,
                  inequality_inconsistency_cache_base* present_branch,
                  inequality_inconsistency_cache_base* non_present_branch)
        : m_node(node),
          m_inequality(inequality),
          m_present_branch(present_branch),
          m_non_present_branch(non_present_branch)
      {}
 
      ~inequality_inconsistency_cache_base()
      {
        if (m_present_branch!=nullptr)
        {
          delete m_present_branch;
        }
        if (m_non_present_branch!=nullptr)
        {
          delete m_non_present_branch;
        }
      }
  };
 
  class inequality_inconsistency_cache
  {
    protected:
      inequality_inconsistency_cache_base* m_cache;
 
      inequality_inconsistency_cache(const inequality_inconsistency_cache& )=delete;
      inequality_inconsistency_cache& operator=(const inequality_consistency_cache& )=delete;
 
    public:
 
      inequality_inconsistency_cache()
        : m_cache(new inequality_inconsistency_cache_base(false_end_node))
      {}
 
      ~inequality_inconsistency_cache()
      {
        if (m_cache!=nullptr)
        {
          delete m_cache;
        }
      }
 
      bool is_inconsistent(const std::vector < linear_inequality >& inequalities_in_) const
      {
        std::set < linear_inequality > inequalities_in(inequalities_in_.begin(),inequalities_in_.end());
        const inequality_inconsistency_cache_base* current_root=m_cache;
        for(const linear_inequality& l: inequalities_in)
        {
          /* First walk down the three until an endnode is found
             that with l<=current_root.m_inequality. */
          while (current_root->m_node==intermediate_node && l>current_root->m_inequality)
          {
            current_root=current_root->m_non_present_branch;
          }
          if (current_root->m_node==intermediate_node)
          {
            if (l==current_root->m_inequality)
            {
              current_root=current_root->m_present_branch;
            }
            assert(current_root->m_node!=intermediate_node || l<current_root->m_inequality);
          }
          else
          {
            return current_root->m_node==true_end_node;
          }
        }
        return current_root->m_node==true_end_node;
      }
 
      void add_inconsistent_inequality_set(const std::vector < linear_inequality >& inequalities_in_)
      {
        std::set < linear_inequality > inequalities_in(inequalities_in_.begin(),inequalities_in_.end());
        inequality_inconsistency_cache_base** current_root=&m_cache;
        for(const linear_inequality& l: inequalities_in)
        {
          /* First walk down the tree until an endnode is found
                that with l<=current_root->m_inequality. */
          while ((*current_root)->m_node==intermediate_node && l>(*current_root)->m_inequality)
          {
            current_root=&((*current_root)->m_non_present_branch);
          }
          if ((*current_root)->m_node==intermediate_node)
          {
            if (l==(*current_root)->m_inequality)
            {
              current_root=&((*current_root)->m_present_branch);
              assert((*current_root)->m_node!=intermediate_node || l<(*current_root)->m_inequality);
            }
            else
            {
              // Add the node.
              inequality_inconsistency_cache_base* new_false_node = new inequality_inconsistency_cache_base(false_end_node);
              inequality_inconsistency_cache_base* new_node = new inequality_inconsistency_cache_base(intermediate_node,l,new_false_node,*current_root);
              *current_root=new_node;
              current_root = &(new_node->m_present_branch);
            }
          }
          else
          {
            if ((*current_root)->m_node==true_end_node)
            {
              // A shorter sequence than the linear inequality set is already inconsistent.
              // This should not occur, assuming that the linear inequality sequence is checked
              // in in this cache, before being proven inconsistent.
              assert(0);
            }
            else
            {
              // Add the remaining sequence.
              inequality_inconsistency_cache_base* new_false_node= new inequality_inconsistency_cache_base(false_end_node);
              inequality_inconsistency_cache_base* new_node = new inequality_inconsistency_cache_base(intermediate_node,l,new_false_node,*current_root);
              *current_root=new_node;
              current_root = &(new_node->m_present_branch);
            }
          }
        }
        // At this point the sequence of inequalities has been explored, but the tree has not ended.
        // We expect the current node to be a true_end_node. If not, we replace it by one.
        if ((*current_root)->m_node!=true_end_node)
        {
          assert(*current_root!=nullptr);
          delete *current_root;
          *current_root=new inequality_inconsistency_cache_base(true_end_node);
        }
      }
  };
 
  class inequality_consistency_cache
  {
    protected:
      inequality_inconsistency_cache_base* m_cache;
 
      inequality_consistency_cache(const inequality_consistency_cache& )=delete;
      inequality_consistency_cache& operator=(const inequality_consistency_cache& )=delete;
 
    public:
 
      inequality_consistency_cache()
        : m_cache(new inequality_inconsistency_cache_base(false_end_node))
      {
      }
 
      ~inequality_consistency_cache()
      {
        if (m_cache!=nullptr)
        {
          delete m_cache;
        }
      }
 
      // Sort the vector inequalities_in if not sorted.
      bool is_consistent(const std::vector < linear_inequality >& inequalities_in_) const
      {
        std::set < linear_inequality > inequalities_in(inequalities_in_.begin(),inequalities_in_.end());
        inequality_inconsistency_cache_base* current_root=m_cache;
        for(std::set < linear_inequality >::const_iterator i=inequalities_in.begin(); i!=inequalities_in.end(); ++i)
        {
          while (current_root->m_node==intermediate_node && *i>current_root->m_inequality)
          {
            current_root=current_root->m_non_present_branch;
          }
          if (current_root->m_node==intermediate_node)
          {
            if (*i==current_root->m_inequality)
            {
              current_root=current_root->m_present_branch;
            }
            else
            {
              return false; // there are more inequalities than available in the tree. We know nothing about it being consistent.
            }
            assert(current_root->m_node!=intermediate_node || *i<current_root->m_inequality);
          }
          else
          {
            return current_root->m_node!=false_end_node && i==inequalities_in.end();
          }
        }
        return true;
      }
 
      void add_consistent_inequality_set(const std::vector < linear_inequality >& inequalities_in_)
      {
        std::set < linear_inequality > inequalities_in(inequalities_in_.begin(),inequalities_in_.end());
        inequality_inconsistency_cache_base** current_root=&m_cache;
        for(const linear_inequality& l: inequalities_in)
        {
          /* First walk down the three until an endnode is found
             with l<=current_root->m_inequality. */
          while ((*current_root)->m_node==intermediate_node && l>(*current_root)->m_inequality)
          {
            current_root=&((*current_root)->m_non_present_branch);
          }
          if ((*current_root)->m_node==intermediate_node)
          {
            if (l==(*current_root)->m_inequality)
            {
              current_root=&((*current_root)->m_present_branch);
              assert((*current_root)->m_node!=intermediate_node || l<(*current_root)->m_inequality);
            }
            else
            {
              // Add the node.
              inequality_inconsistency_cache_base* new_true_node = new inequality_inconsistency_cache_base(true_end_node);
              inequality_inconsistency_cache_base* new_node = new inequality_inconsistency_cache_base(intermediate_node,l,new_true_node,*current_root);
              *current_root=new_node;
              current_root = &(new_node->m_present_branch);
            }
          }
          else
          {
            // Add the remaining sequence.
            inequality_inconsistency_cache_base* new_true_node=new inequality_inconsistency_cache_base(true_end_node);
            inequality_inconsistency_cache_base* new_node = new inequality_inconsistency_cache_base(intermediate_node,l,new_true_node,*current_root);
            *current_root=new_node;
            current_root = &(new_node->m_present_branch);
          }
        }
      }
  };
 
}
 
 
inline bool is_inconsistent(
  const std::vector < linear_inequality >& inequalities_in,
  const rewriter& r,
  const bool use_cache/*=true*/)
{
  // Transform the linear inequalities into a vector of equalities and a
  // sequence of constraints on variables. All variables, including
  // those that will be generated as slack variables will have values indicated
  // by beta, which must lie between the lowerbounds and the upperbounds.
 
  // First remove all equalities by Gauss elimination and make a fresh variable
  // generator.
 
  mCRL2log(log::trace) << "Starting an inconsistency check on " + pp_vector(inequalities_in) << "\n";
 
  static detail::inequality_inconsistency_cache inconsistency_cache;
  static detail::inequality_consistency_cache consistency_cache;
 
  if (use_cache && consistency_cache.is_consistent(inequalities_in))
  {
    assert(!is_inconsistent(inequalities_in,r,false));
    return false;
  }
  if (use_cache && inconsistency_cache.is_inconsistent(inequalities_in))
  {
    assert(is_inconsistent(inequalities_in,r,false));
    return true;
  }
  // The required data structures
  std::map < variable,data_expression > lowerbounds;
  std::map < variable,data_expression > upperbounds;
  std::map < variable,data_expression > beta;
  std::map < variable,data_expression > lowerbounds_delta_correction;
  std::map < variable,data_expression > upperbounds_delta_correction;
  std::map < variable,data_expression > beta_delta_correction;
  std::set < variable > non_basic_variables;
  std::set < variable > basic_variables;
  std::map < variable, detail::lhs_t > working_equalities;
 
  set_identifier_generator fresh_variable_name;
 
  for (std::vector < linear_inequality >::const_iterator i=inequalities_in.begin();
       i!=inequalities_in.end(); ++i)
  {
    if (i->is_false(r))
    {
      mCRL2log(log::trace) << "Inconsistent, because linear inequalities contains an inconsistent inequality\n";
      if (use_cache)
      {
        inconsistency_cache.add_inconsistent_inequality_set(inequalities_in); // Necessary? Only false should be added.
        assert(inconsistency_cache.is_inconsistent(inequalities_in));
      }
      return true;
    }
    i->add_variables(non_basic_variables);
    for (detail::lhs_t::const_iterator j=i->lhs_begin();
         j!=i->lhs_end(); ++j)
    {
      fresh_variable_name.add_identifier(j->variable_name().name());
    }
  }
 
  std::vector < linear_inequality > inequalities;
  std::vector < linear_inequality > equalities;
  non_basic_variables=
    gauss_elimination(inequalities_in,
                      equalities,      // Store all resulting equalities here.
                      inequalities,    // Store all resulting non equalities here.
                      non_basic_variables.begin(),
                      non_basic_variables.end(),
                      r);
 
  assert(equalities.size()==0); // There are no resulting equalities left.
  non_basic_variables.clear(); // gauss_elimination has removed certain variables. So, we reconstruct the non
  // basic variables again below.
 
  mCRL2log(log::trace) << "Resulting equalities " << pp_vector(equalities) << "\n";
  mCRL2log(log::trace) << "Resulting inequalities " << pp_vector(inequalities) << "\n";
 
  // Now bring the linear equalities in the basic form described
  // in the article by Bruno Dutertre and Leonardo de Moura.
 
  // First set lower and upperbounds, and introduce slack variables
  // if required.
  for (std::vector < linear_inequality >::iterator i=inequalities.begin();
       i!=inequalities.end(); ++i)
  {
    mCRL2log(log::trace) << "Investigate inequality: " << ":=" << pp(*i) << " ||  " << pp(i->lhs()) << "\n";
    if (i->is_false(r))
    {
      mCRL2log(log::trace) << "Inconsistent, because linear inequalities contains an inconsistent inequality after Gauss elimination\n";
      if (use_cache)
      {
        inconsistency_cache.add_inconsistent_inequality_set(inequalities_in); // Necessary? Only false should be added.
        assert(inconsistency_cache.is_inconsistent(inequalities_in));
      }
      return true;
    }
    if (!i->is_true(r))  // This inequality is redundant and can be skipped.
    {
      assert(i->comparison()!=detail::equal);
      assert(i->lhs().size()>0); // this signals a redundant or an inconsistent inequality.
      i->add_variables(non_basic_variables);
 
      if (i->lhs().size()==1)  // the left hand side consists of a single variable.
      {
        variable v=i->lhs_begin()->variable_name();
        data_expression factor=i->lhs_begin()->factor();
        assert(factor!=real_zero());
        data_expression bound=rewrite_with_memory(real_divides(i->rhs(),factor),r);
        if (is_positive(factor,r))
        {
          // The inequality has the shape factor*v<=c or factor*v<c with factor positive
          if ((upperbounds.count(v)==0) ||
              (rewrite_with_memory(less(bound,upperbounds[v]),r)==sort_bool::true_()))
          {
            upperbounds[v]=bound;
            upperbounds_delta_correction[v]=
              ((i->comparison()==detail::less)?real_minus_one():real_zero());
 
          }
          else
          {
            if (bound==upperbounds[v])
            {
              upperbounds_delta_correction[v]=
                min(upperbounds_delta_correction[v],
                    ((i->comparison()==detail::less)?real_minus_one():real_zero()),r);
            }
          }
        }
        else
        {
          // The inequality has the shape factor*v<=c or factor*v<c with factor negative
          if ((lowerbounds.count(v)==0) ||
              (rewrite_with_memory(less(lowerbounds[v],bound),r)==sort_bool::true_()))
          {
            lowerbounds[v]=bound;
            lowerbounds_delta_correction[v]=
              ((i->comparison()==detail::less)?real_one():real_zero());
          }
          else
          {
            if (bound==lowerbounds[v])
            {
              lowerbounds_delta_correction[v]=
                max(lowerbounds_delta_correction[v],
                    ((i->comparison()==detail::less)?real_one():real_zero()),r);
            }
          }
        }
      }
      else
      {
        // The inequality has more than one variable at the left hand side.
        // We transform it into an equation with a new slack variable.
        variable new_basic_variable(fresh_variable_name("slack_var"), sort_real::real_());
        basic_variables.insert(new_basic_variable);
        upperbounds[new_basic_variable]=i->rhs();
        upperbounds_delta_correction[new_basic_variable]=
          ((i->comparison()==detail::less)?real_minus_one():real_zero());
        working_equalities[new_basic_variable]=i->lhs();
        mCRL2log(log::trace) << "New slack variable: " << pp(new_basic_variable) << ":=" << pp(*i) << "   " << pp(i->lhs()) << "\n";
      }
    }
  }
  // Now set the values for beta:
  // The beta values for the non basic variables must satisfy the lower and
  // upperbounds.
  for (std::set < variable >::const_iterator i=non_basic_variables.begin();
       i!=non_basic_variables.end(); ++i)
  {
    if (lowerbounds.count(*i)>0)
    {
      if ((upperbounds.count(*i)>0) &&
          ((rewrite_with_memory(less(upperbounds[*i],lowerbounds[*i]),r)==sort_bool::true_()) ||
           ((upperbounds[*i]==lowerbounds[*i]) &&
            (rewrite_with_memory(less(upperbounds_delta_correction[*i],lowerbounds_delta_correction[*i]),r)==sort_bool::true_()))))
      {
        mCRL2log(log::trace) << "Inconsistent, preprocessing " << pp(*i) << "\n";
        if (use_cache)
        {
          inconsistency_cache.add_inconsistent_inequality_set(inequalities_in);
          assert(inconsistency_cache.is_inconsistent(inequalities_in));
        }
        return true; // Inconsistent.
      }
      beta[*i]=lowerbounds[*i];
      beta_delta_correction[*i]=lowerbounds_delta_correction[*i];
    }
    else if (upperbounds.count(*i)>0)
    {
      beta[*i]=upperbounds[*i];
      beta_delta_correction[*i]=upperbounds_delta_correction[*i];
    }
    else // *i has neither a lower or an upperbound
    {
      beta[*i]=real_zero();
      beta_delta_correction[*i]=real_zero();
    }
    mCRL2log(log::trace) << "(2) beta[" << pp(*i) << "]=" << pp(beta[*i])<< "+delta*" << pp(beta_delta_correction[*i]) <<"\n";
  }
 
  // Subsequently set the values for the basic variables
  for (std::set < variable >::const_iterator i=basic_variables.begin();
       i!=basic_variables.end(); ++i)
  {
    beta[*i]=working_equalities[*i].evaluate(make_map_substitution(beta),r);
    beta_delta_correction[*i]=working_equalities[*i].
                              evaluate(make_map_substitution(beta_delta_correction),r);
    mCRL2log(log::trace) << "(3) beta[" << pp(*i) << "]=" << pp(beta[*i])<< "+delta*" << pp(beta_delta_correction[*i]) <<"\n";
  }
 
  // Now the basic data structure has been set up.
  // We must find the first basic variable that does not satisfy its
  // upper and bounds. This is essentially the check algorithm in the
  // article by Bruno Dutertre and Leonardo de Moura.
 
  for (; true ;)
  {
    // select the smallest basic variable that does not satisfy the bounds.
    bool found=false;
    bool lowerbound_violation = false;
    variable xi;
    for (std::set < variable > :: const_iterator i=basic_variables.begin() ;
         i!=basic_variables.end() ; ++i)
    {
      mCRL2log(log::trace) << "Evaluate start\n";
      assert(!found);
      data_expression value=beta[*i]; // working_equalities[*i].evaluate(beta,r);
      data_expression value_delta_correction=beta_delta_correction[*i]; // working_equalities[*i].evaluate(beta_delta_correction,r);
      mCRL2log(log::trace) << "Evaluate end\n";
      if ((upperbounds.count(*i)>0) &&
          ((rewrite_with_memory(less(upperbounds[*i],value),r)==sort_bool::true_()) ||
           ((upperbounds[*i]==value) &&
            (rewrite_with_memory(less(upperbounds_delta_correction[*i],value_delta_correction),r)==sort_bool::true_()))))
      {
        // The value of variable *i does not satisfy its upperbound. This must
        // be corrected using pivoting.
        mCRL2log(log::trace) << "Upperbound violation " << pp(*i) << "  bound: " << pp(upperbounds[*i]) << "\n";
        found=true;
        xi=*i;
        lowerbound_violation=false;
        break;
      }
      else if ((lowerbounds.count(*i)>0) &&
               ((rewrite_with_memory(less(value,lowerbounds[*i]),r)==sort_bool::true_()) ||
                ((lowerbounds[*i]==value) &&
                 (rewrite_with_memory(less(value_delta_correction,lowerbounds_delta_correction[*i]),r)==sort_bool::true_()))))
      {
        // The value of variable *i does not satisfy its upperbound. This must
        // be corrected using pivoting.
        mCRL2log(log::trace) << "Lowerbound violation " << pp(*i) << "  bound: " << pp(lowerbounds[*i]) << "\n";
        found=true;
        xi=*i;
        lowerbound_violation=true;
        break;
      }
    }
    if (!found)
    {
      // The inequalities are consistent. Return false.
      mCRL2log(log::trace) << "Consistent while pivoting\n";
      if (use_cache)
      {
        consistency_cache.add_consistent_inequality_set(inequalities_in);
        assert(consistency_cache.is_consistent(inequalities_in));
      }
      return false;
    }
 
    mCRL2log(log::trace) << "The smallest basic variable that does not satisfy the bounds is " << pp(xi) << "\n";
    if (lowerbound_violation)
    {
      mCRL2log(log::trace) << "Lowerbound violation \n";
      // select the smallest non-basic variable with which pivoting can take place.
      bool found=false;
      const detail::lhs_t& lhs=working_equalities[xi];
      for (detail::lhs_t::const_iterator xj_it=lhs.begin(); xj_it!=lhs.end(); ++xj_it)
      {
        const variable xj=xj_it->variable_name();
        mCRL2log(log::trace) << pp(xj) << "  --  " << pp(xj_it->factor()) << "\n";
        if ((is_positive(xj_it->factor(),r) &&
             ((upperbounds.count(xj)==0) ||
              ((rewrite_with_memory(less(beta[xj],upperbounds[xj]),r)==sort_bool::true_())||
               ((beta[xj]==upperbounds[xj])&& (rewrite_with_memory(less(beta_delta_correction[xj],upperbounds_delta_correction[xj]),r)==sort_bool::true_()))))) ||
            (is_negative(xj_it->factor(),r) &&
             ((lowerbounds.count(xj)==0) ||
              ((rewrite_with_memory(greater(beta[xj],lowerbounds[xj]),r)==sort_bool::true_())||
               ((beta[xj]==lowerbounds[xj]) && (rewrite_with_memory(greater(beta_delta_correction[xj],lowerbounds_delta_correction[xj]),r)==sort_bool::true_()))))))
        {
          found=true;
          pivot_and_update(xi,xj,lowerbounds[xi],lowerbounds_delta_correction[xi],
                           beta, beta_delta_correction,
                           basic_variables,working_equalities,r);
          break;
        }
      }
      if (!found)
      {
        // The inequalities are inconsistent.
        mCRL2log(log::trace) << "Inconsistent while pivoting\n";
        if (use_cache)
        {
          inconsistency_cache.add_inconsistent_inequality_set(inequalities_in);
          assert(inconsistency_cache.is_inconsistent(inequalities_in));
        }
        return true;
      }
 
    }
    else  // Upperbound violation.
    {
      mCRL2log(log::trace) << "Upperbound violation \n";
      // select the smallest non-basic variable with which pivoting can take place.
      bool found=false;
      for (detail::lhs_t::const_iterator xj_it=working_equalities[xi].begin();
           xj_it!=working_equalities[xi].end(); ++xj_it)
      {
        const variable xj=xj_it->variable_name();
        mCRL2log(log::trace) << pp(xj) << "  --  " << pp(xj_it->factor()) <<  " POS " << is_positive(xj_it->factor(),r) << "\n";
        if ((is_negative(xj_it->factor(),r) &&
             ((upperbounds.count(xj)==0) ||
              ((rewrite_with_memory(less(beta[xj],upperbounds[xj]),r)==sort_bool::true_()) ||
               ((beta[xj]==upperbounds[xj])&& (rewrite_with_memory(less(beta_delta_correction[xj],upperbounds_delta_correction[xj]),r)==sort_bool::true_()))))) ||
            (is_positive(xj_it->factor(),r) &&
             ((lowerbounds.count(xj)==0) ||
              ((rewrite_with_memory(greater(beta[xj],lowerbounds[xj]),r)==sort_bool::true_()) ||
               ((beta[xj]==lowerbounds[xj]) && (rewrite_with_memory(greater(beta_delta_correction[xj],lowerbounds_delta_correction[xj]),r)==sort_bool::true_()))))))
        {
          found=true;
          pivot_and_update(xi,xj,upperbounds[xi],upperbounds_delta_correction[xi],
                           beta,beta_delta_correction,
                           basic_variables,working_equalities,r);
          break;
        }
      }
      if (!found)
      {
        // The inequalities are inconsistent.
        mCRL2log(log::trace) << "Inconsistent while pivoting (1)\n";
        if (use_cache)
        {
          inconsistency_cache.add_inconsistent_inequality_set(inequalities_in);
          assert(inconsistency_cache.is_inconsistent(inequalities_in));
        }
        return true;
      }
    }
  }
}
 
//---------------------------------------------------------------------------------------------------
 
 
 
template < class Variable_iterator >
std::set < variable >  gauss_elimination(
  const std::vector < linear_inequality >& inequalities,
  std::vector < linear_inequality >& resulting_equalities,
  std::vector < linear_inequality >& resulting_inequalities,
  Variable_iterator variables_begin,
  Variable_iterator variables_end,
  const rewriter& r)
{
  std::set < variable >  remaining_variables;
 
  // First copy equalities to the resulting_equalities and the inequalites to resulting_inequalities.
  for (std::vector < linear_inequality > ::const_iterator j = inequalities.begin(); j != inequalities.end(); ++j)
  {
    if (j->is_false(r))
    {
      // The input contains false. Return false and stop.
      resulting_equalities.clear();
      resulting_inequalities.clear();
      resulting_inequalities.push_back(linear_inequality());
      return remaining_variables;
    }
    else if (!j->is_true(r)) // Do not consider redundant equations.
    {
      if (j->comparison()==detail::equal)
      {
        resulting_equalities.push_back(*j);
      }
      else
      {
        resulting_inequalities.push_back(*j);
      }
    }
  }
 
  // Now find out whether there are variables that occur in an equality, so
  // that we can perform gauss elimination.
  for (Variable_iterator i = variables_begin; i != variables_end; ++i)
  {
    std::size_t j;
    for (j=0; j<resulting_equalities.size(); ++j)
    {
      bool check_equalities_for_redundant_inequalities(false);
      std::set < variable > vars;
      resulting_equalities[j].add_variables(vars);
      if (vars.count(*i)>0)
      {
        // Equality *j contains data variable *i.
        // Perform gauss elimination, and break the loop.
 
        for (std::size_t k = 0; k < resulting_inequalities.size();)
        {
          resulting_inequalities[k]=subtract(resulting_inequalities[k],
                                             resulting_equalities[j],
                                             resulting_inequalities[k].get_factor_for_a_variable(*i),
                                             resulting_equalities[j].get_factor_for_a_variable(*i),
                                             r);
          if (resulting_inequalities[k].is_false(r))
          {
            // The input is inconsistent. Return false.
            resulting_equalities.clear();
            resulting_inequalities.clear();
            resulting_inequalities.push_back(linear_inequality());
            remaining_variables.clear();
            return remaining_variables;
          }
          else if (resulting_inequalities[k].is_true(r))
          {
            // Inequality k has become redundant, and can be removed.
            if ((k+1)<resulting_inequalities.size())
            {
              resulting_inequalities[k].swap(resulting_inequalities.back());
            }
            resulting_inequalities.pop_back();
          }
          else
          {
            ++k;
          }
        }
 
        for (std::size_t k = 0; k<resulting_equalities.size();)
        {
          if (k==j)
          {
            ++k;
          }
          else
          {
            resulting_equalities[k]=subtract(
              resulting_equalities[k],
              resulting_equalities[j],
              resulting_equalities[k].get_factor_for_a_variable(*i),
              resulting_equalities[j].get_factor_for_a_variable(*i),
              r);
            if (resulting_equalities[k].is_false(r))
            {
              // The input is inconsistent. Return false.
              resulting_equalities.clear();
              resulting_inequalities.clear();
              resulting_inequalities.push_back(linear_inequality());
              remaining_variables.clear();
              return remaining_variables;
            }
            else if (resulting_equalities[k].is_true(r))
            {
              // Equality k has become redundant, and can be removed.
              if (j+1==resulting_equalities.size())
              {
                // It is not possible to move move the last element of resulting
                // inequalities to position k, because j is at this last position.
                // Hence, we must recall to check the resulting_equalities for inequalities
                // that are true.
                check_equalities_for_redundant_inequalities=true;
              }
              else
              {
                if ((k+1)<resulting_equalities.size())
                {
                  resulting_equalities[k].swap(resulting_equalities.back());
                }
                resulting_equalities.pop_back();
              }
            }
            else
            {
              ++k;
            }
          }
        }
 
        // Remove equation j.
 
        if (j+1<resulting_equalities.size())
        {
          resulting_equalities[j].swap(resulting_equalities.back());
        }
        resulting_equalities.pop_back();
 
        // If there are unremoved resulting equalities, remove them now.
        if (check_equalities_for_redundant_inequalities)
        {
          for (std::size_t k = 0; k<resulting_equalities.size();)
          {
            if (resulting_equalities[k].is_true(r))
            {
              // Equality k is redundant, and can be removed.
              if ((k+1)<resulting_equalities.size())
              {
                resulting_equalities[k].swap(resulting_equalities.back());
              }
              resulting_equalities.pop_back();
            }
            else
            {
              ++k;
            }
          }
        }
      }
    }
    remaining_variables.insert(*i);
  }
 
  return remaining_variables;
}
 
// The introduction of the function rewrite_with_memory using a
// hash table here is a temporary trick, to boost
// performance, which is slow due to translations necessary from and to
// rewrite format.
 
inline data_expression rewrite_with_memory(
  const data_expression& t,const rewriter& r)
{
  static std::map < data_expression, data_expression > rewrite_hash_table;
  std::map < data_expression, data_expression > :: iterator i=rewrite_hash_table.find(t);
  if (i==rewrite_hash_table.end())
  {
    data_expression t1=r(t);
    rewrite_hash_table.insert(std::make_pair(t, t1));
    return t1;
  }
  return i->second;
}
 
} // namespace data
 
} // namespace mcrl2
 
#endif // MCRL2_DATA_LINEAR_INEQUALITY_H